Against the backdrop of global infrastructure upgrading and the growing demand for high-performance asphalt materials (e.g., SBS-modified asphalt for high-speed highways, rubber-modified asphalt for urban roads), modified asphalt equipment is shifting from "manual operation-driven" to "intelligent system-led." The core of this transformation lies in three key technologies: PLC automatic control (realizing precise, stable process execution), IoT monitoring (enabling full-life-cycle visibility of equipment and production), and adaptive adjustment of formula parameters (adapting to raw material variations and product requirements dynamically). This article explores how these three technologies are reshaping the development of modified asphalt equipment, and analyzes their application value and future evolution directions.

1. PLC Automatic Control: The "Brain" of Intelligent Production, Ensuring Precision and Stability

Traditional modified asphalt production relies heavily on manual operation—workers adjust grinding time, stirring speed, and temperature based on experience, leading to inconsistent product quality (e.g., SBS modifier dispersion uniformity varying by ±5%) and high dependency on skilled labor. PLC (Programmable Logic Controller) automatic control solves these pain points by integrating process logic into a digital system, achieving "standardized, precise, and fatigue-free" production.

1.1 Core Application: Full-Process Automated Execution

PLC systems for modified asphalt equipment are customized to match the production workflow (raw material feeding → mixing → grinding → development → storage), with key functions including:

Precise Raw Material Metering: Connecting to weight sensors (accuracy ±0.1%) on asphalt tanks, modifier hoppers, and additive tanks, the PLC automatically calculates and controls the feeding amount according to the formula (e.g., 3.5% SBS modifier for 10 tons of base asphalt). It eliminates manual weighing errors (which can reach ±2%) and ensures the modifier ratio is consistent with the design value.

Adaptive Process Parameter Regulation: During grinding, the PLC monitors the colloid mill’s current (reflecting load) and the asphalt’s viscosity (measured by an online viscometer). If viscosity exceeds the set range (e.g., >3000 mPa·s for SBS-modified asphalt), it automatically increases the grinding speed (from 3000 r/min to 3500 r/min) or extends the grinding time (by 2-3 minutes) to improve modifier dispersion. During stirring, it adjusts the agitator speed (200-500 r/min) based on temperature (e.g., 170-180℃ for development stage), preventing asphalt coking due to overheating or insufficient mixing due to low speed.

Fault Self-Protection and Shutdown: The PLC connects to over 20 sensors (temperature, pressure, level, current) across the equipment. If abnormal conditions occur—such as asphalt tank level below the minimum threshold (triggering "no-load protection"), colloid mill current exceeding the overload limit (110% of rated current), or heating oil temperature exceeding 200℃ (coking risk)—the system immediately stops the corresponding process, sounds an alarm, and displays the fault location on the HMI (Human-Machine Interface), reducing accident risks by 80% compared to manual monitoring.

1.2 Technical Advantages: Elevating Production Efficiency and Quality Consistency

Quality Uniformity: PLC control reduces the variation in modifier dispersion uniformity from ±5% (manual operation) to ±1.5%, ensuring that key indicators (e.g., penetration, ductility) of modified asphalt meet national standards (e.g., China’s GB/T 14833-2011) stably.

Production Efficiency: By optimizing process intervals (e.g., reducing the waiting time between feeding and grinding from 10 minutes to 3 minutes) and avoiding rework due to quality issues, PLC automatic control increases production capacity by 15%-20% (e.g., a 50 t/h equipment can reach 57.5-60 t/h).

Labor Cost Reduction: A single PLC-controlled production line requires only 1-2 operators (for supervision and exception handling), compared to 3-4 workers for traditional manual lines, cutting labor costs by 50% annually.

2. IoT Monitoring: The "Nervous System" of Equipment, Enabling Full-Life-Cycle Visibility

Modified asphalt equipment often operates in harsh environments (e.g., construction sites with dust, temperature fluctuations) and faces challenges such as "invisible faults" (e.g., internal wear of colloid mill bearings) and "uncontrollable off-site operations" (e.g., mobile equipment for road repair). IoT (Internet of Things) monitoring solves these issues by connecting equipment, sensors, and cloud platforms, realizing "real-time status tracking, remote diagnosis, and predictive maintenance."

2.1 Key Application Scenarios

Real-Time Remote Monitoring: IoT modules (e.g., 4G/5G, LoRa) installed on the equipment transmit data from sensors (temperature, pressure, speed, vibration) to a cloud platform every 10-30 seconds. Managers can view production status (e.g., current output, formula used), equipment parameters (e.g., colloid mill vibration amplitude, motor temperature), and alarm information via a mobile app or web terminal—even for mobile equipment working in remote mountainous areas. For example, if a mobile modified asphalt unit’s heating tube temperature drops abnormally (indicating a blockage), the platform immediately sends an alert to the maintenance team, avoiding production halts.

Predictive Maintenance Based on Big Data: The cloud platform accumulates equipment operation data (e.g., colloid mill working hours, vibration frequency, bearing temperature) and uses algorithms to analyze wear trends. For instance, when the bearing vibration amplitude of a colloid mill exceeds 0.15 mm (a threshold indicating 80% of its service life), the system predicts that the bearing will fail in 15-20 days and sends a maintenance reminder. This replaces "planned maintenance" (which may replace parts prematurely or miss faults) with "condition-based maintenance," reducing unplanned downtime by 40% and extending the service life of key components (e.g., colloid mill bearings) by 20%.

Production Data Traceability: The IoT system records every batch of modified asphalt production data (raw material sources, formula parameters, process temperatures, quality test results) and stores it in the cloud for 3-5 years. If a quality complaint arises (e.g., asphalt ductility failing a road test), engineers can trace the production process of the problematic batch in 5 minutes, identify the root cause (e.g., insufficient grinding time), and avoid similar issues. This meets the traceability requirements of infrastructure projects (e.g., China’s "Smart Highway" construction standards).

2.2 Technical Evolution: From "Data Collection" to "Intelligent Analysis"

Current IoT monitoring focuses on "data transmission and display," while future systems will integrate AI algorithms for deeper analysis. For example, by comparing the vibration data of multiple colloid mills of the same model, the platform can identify "abnormal but not faulty" signals (e.g., a slight increase in vibration frequency) and recommend preventive measures (e.g., cleaning the mill gap), further reducing maintenance costs.